- (Topic 6)
A JSON object is loaded into a column named data using a Snowflake variant datatype. The root node of the object is BIKE. The child attribute for this root node is BIKEID. Which statement will allow the user to access BIKEID?

1. A. select data:BIKEID
2. B. select data.BIKE.BIKEID
3. C. select data:BIKE.BIKEID
4. D. select data:BIKE:BIKEID

Correct Answer: C
In Snowflake, when accessing elements within a JSON object stored in a variant column, the correct syntax involves using a colon (:) to navigate the JSON structure. TheBIKEID attribute, which is a child of theBIKEroot node in the JSON object, is accessed using data:BIKE.BIKEID. This syntax correctly references the path through the JSON object, utilizing the colon for JSON field access and dot notation to traverse the hierarchy within the variant structure.References:Snowflake documentation on accessing semi-structured data, which outlines how to use the colon and dot notations for navigating JSON structures stored in variant columns.

- (Topic 6)
A clustering key was defined on a table, but It is no longer needed. How can the key be removed?

1. A. ALTER TABLE <TABLE NAME> PURGE CLUSTERING KEY
2. B. ALTER TABLE <TABLE NAME> DELETE CLUSTERING KEY
3. C. ALTER TABLE <TABLE NAME> DROP CLUSTERING KEY
4. D. ALTER TABLE <TABLE NAME> REMOVE CLUSTERING KEY

Correct Answer: C
To remove a clustering key that was previously defined on a table in Snowflake, the correct SQL command isALTER TABLE <TABLE NAME> DROP CLUSTERING KEY. This command removes the existing clustering key from the table, after which Snowflake will no longer re-cluster data based on that key during maintenance operations or after data loading operations.
Reference: Snowflake Documentation on altering tables, specifically the section on
modifying clustering keys: https://docs.snowflake.com/en/sql-reference/sql/alter- table.html#modifying-clustering-keys

- (Topic 6)
How can a Snowsight user change a Standard virtual warehouse to a Snowpark-optimized virtual warehouse?

1. A. Use the ALTER WAREHOUSE command on an active Standard virtual warehouse
2. B. Use the alter warehouse command on an active Snowpark-optimized warehouse.
3. C. Use the ALTER warehouse command on a suspended Standard virtual warehouse.
4. D. Use the ALTER WAREHOUSE command on a suspended Snowpark-optimized warehouse.

Correct Answer: C
To change a Standard virtual warehouse to a Snowpark-optimized virtual warehouse, the warehouse must be in a suspended state. This ensures that no operations are disrupted during the modification process.
✑ Suspend the Warehouse:Ensure that the warehouse is suspended.
ALTER WAREHOUSE my_warehouse SUSPEND;
✑ Alter the Warehouse:Modify the warehouse to be Snowpark-optimized. ALTER WAREHOUSE my_warehouse SET WAREHOUSE_TYPE = 'SNOWPARK-
OPTIMIZED';
✑ Resume the Warehouse:Resume the warehouse to make it operational. ALTER WAREHOUSE my_warehouse RESUME;
References:
✑ Snowflake Documentation: Creating Snowpark-Optimized Warehouses
✑ Snowflake Documentation: ALTER WAREHOUSE

- (Topic 5)
When floating-point number columns are unloaded to CSV or JSON files, Snowflake truncates the values to approximately what?

1. A. (12,2)
2. B. (10,4)
3. C. (14,8)
4. D. (15,9)

Correct Answer: D
When unloading floating-point number columns to CSV or JSON files, Snowflake truncates the values to approximately 15 significant digits with 9 digits following the decimal point, which can be represented as (15,9). This ensures a balance between accuracy and efficiency in representing floating-point numbers in text-based formats, which is essential for data interchange and processing applications that consume these files. References:
✑ Snowflake Documentation: Data Unloading Considerations

- (Topic 1)
What is a machine learning and data science partner within the Snowflake Partner Ecosystem?

1. A. Informatica
2. B. Power Bl
3. C. Adobe
4. D. Data Robot

Correct Answer: D
Data Robot is recognized as a machine learning and data science partner within the Snowflake Partner Ecosystem. It provides an enterprise AI platform that enables users to build and deploy accurate predictive models quickly. As a partner, Data Robot integrates with Snowflake to enhance data science capabilities2.
References:
✑ [COF-C02] SnowPro Core Certification Exam Study Guide
✑ Snowflake Documentation on Machine Learning & Data Science Partners
https://docs.snowflake.com/en/user-guide/ecosystem-analytics.html